Analysis of different propagation models for the estimation of the topside ionosphere and plasmasphere with an ensemble Kalman filter

Abstract

Abstract. The accuracy and availability of satellite-based applications, like Global Navigation Satellite System (GNSS) positioning and remote sensing, crucially depend on the knowledge of the ionospheric electron density distribution. The tomography of the ionosphere is one of the major tools for providing links to specific ionospheric corrections and studying and monitoring physical processes in the ionosphere and plasmasphere. In this work, we apply an ensemble Kalman filter (EnKF) approach for the 4D electron density reconstruction of the topside ionosphere and plasmasphere, with the focus on the investigation of different propagation models, and compare them with the iterative reconstruction technique of simultaneous multiplicative column normalized method plus (SMART+). The slant total electron content (STEC) measurements of 11 low earth orbit (LEO) satellites are assimilated into the reconstructions. We conduct a case study on a global grid with altitudes between 430 and 20 200 km, for two periods of the year 2015, covering quiet to perturbed ionospheric conditions. Particularly the performance of the methods for estimating independent STEC and electron density measurements from the three Swarm satellites is analysed. The results indicate that the methods of EnKF, with exponential decay as the propagation model, and SMART+ perform best, providing, in summary, the lowest residuals.

Global Three‐Dimensional Ionospheric Tomography by Combination of Ground‐Based and Space‐Borne GNSS Data

“…As a result, the background ionosphere must be represented accurately (F. D. S. Prol & Camargo, 2015). Considering that the voxel‐based tomographic model used in this study extends to approximately 5,000 km in altitude and the NeQuick‐2 model provides a more accurate representation of the topside ionosphere (Gerzen et al., 2020; Nava et al., 2008; Wang et al., 2017), the vertical profiles at each hour of the 30 days before the tomographic day that were derived from the NeQuick‐2 model are used to construct an original data set. Specifically, the total number of all vertical profiles from the 36 × 36 = 1,296 vertical bins is 30 × 24 × 1,296 = 933,120.…”

“…The dual‐frequency GNSS receiver for precise orbit determination (POD) onboard the LEO satellite can track up to 8–12 different GNSS satellites in a large spatial volume above orbital altitudes and can observe the ionosphere ahead, behind, and aside of the LEO position (Zakharenkova et al., 2016). Therefore, GNSS data from LEO satellites can provide additional upward looking slant total electron content (STEC) measurements that enable global imaging of the topside ionosphere and plasmasphere with ionospheric tomography (Bust & Mitchell, 2008; Gerzen et al., 2020; Jayawardena et al., 2016; H. Li et al., 2012; F. S. Prol, Hoque, & Ferreira, 2021). To maintain the high accuracy of tomographic reconstructions, the region's ray path coverage must be enhanced using many hours of data.…”

A Review of Voxel-Based Computerized Ionospheric Tomography with GNSS Ground Receivers

“…He et al (2013) [96] presented an algorithm to realize global real-time CIT, while the resolution can still be improved. Gerzen et al (2020) [97] developed a four-dimensional global CIT with an ensemble Kalman filter, while the altitudes were restricted between 430 and 20,200 km. In morphology and dynamics studies of ionosphere and ionospheric monitoring, the global real-time CIT with higher precision and resolution is a continuous goal.…”

Real‐Time Monitoring of Ionosphere VTEC Using Multi‐GNSS Carrier‐Phase Observations and B‐Splines

“…In addition to incorporating precise observations, the selection of the mathematical model describing the spatial distribution of electron content is of great importance. Various models have been introduced for global VTEC representation, for instance, B-Spline series expansion (Schmidt, 2007;Schmidt et al, 2015), spherical harmonic expansion (Schaer, 1999), TEC values on triangular tiles (Mannucci et al, 1998) and grids (Skone, 1999), BMARS (Durmaz & Karslioglu, 2015), thin-plate spline representation (Krypiak-Gregorczyk et al, 2017) as well as multi-dimensional models, see, for example, Farzaneh and Forootan (2017), Gerzen et al (2020), Hernández-Pajares et al (1999, Z. Liu (2004), Limberger (2015), Schmidt et al (2015), and Zeilhofer et al (2009).…”